4 research outputs found
Structural cost-optimal design of sensor networks for distributed estimation
In this letter we discuss cost optimization of sensor networks monitoring
structurally full-rank systems under distributed observability constraint.
Using structured systems theory, the problem is relaxed into two subproblems:
(i) sensing cost optimization and (ii) networking cost optimization. Both
problems are reformulated as combinatorial optimization problems. The sensing
cost optimization is shown to have a polynomial order solution. The networking
cost optimization is shown to be NP-hard in general, but has a polynomial order
solution under specific conditions. A 2-approximation polynomial order
relaxation is provided for general networking cost optimization, which is
applicable in large-scale system monitoring
On the Observability and Controllability of Large-Scale IoT Networks: Reducing Number of Unmatched Nodes via Link Addition
In this paper, we study large-scale networks in terms of observability and
controllability. In particular, we compare the number of unmatched nodes in two
main types of Scale-Free (SF) networks: the Barab{\'a}si-Albert (BA) model and
the Holme-Kim (HK) model. Comparing the two models based on theory and
simulation, we discuss the possible relation between clustering coefficient and
the number of unmatched nodes. In this direction, we propose a new algorithm to
reduce the number of unmatched nodes via link addition. The results are
significant as one can reduce the number of unmatched nodes and therefore
number of embedded sensors/actuators in, for example, an IoT network. This may
significantly reduce the cost of controlling devices or monitoring cost in
large-scale systems
Recovering the Structural Observability of Composite Networks via Cartesian Product
Observability is a fundamental concept in system inference and estimation.
This paper is focused on structural observability analysis of Cartesian product
networks. Cartesian product networks emerge in variety of applications
including in parallel and distributed systems. We provide a structural approach
to extend the structural observability of the constituent networks (referred as
the factor networks) to that of the Cartesian product network. The structural
approach is based on graph theory and is generic. We introduce certain
structures which are tightly related to structural observability of networks,
namely parent Strongly-Connected-Component (parent SCC), parent node, and
contractions. The results show that for particular type of networks (e.g. the
networks containing contractions) the structural observability of the factor
network can be recovered via Cartesian product. In other words, if one of the
factor networks is structurally rank-deficient, using the other factor network
containing a spanning cycle family, then the Cartesian product of the two
nwtworks is structurally full-rank. We define certain network structures for
structural observability recovery. On the other hand, we derive the number of
observer nodes--the node whose state is measured by an output-- in the
Cartesian product network based on the number of observer nodes in the factor
networks. An example illustrates the graph-theoretic analysis in the paper
Minimal Sufficient Conditions for Structural Observability/Controllability of Composite Networks via Kronecker Product
In this paper, we consider composite networks formed from the Kronecker
product of smaller networks. We find the observability and controllability
properties of the product network from those of its constituent smaller
networks. The overall network is modeled as a Linear-Structure-Invariant (LSI)
dynamical system where the underlying matrices have a fixed zero/non-zero
structure but the non-zero elements are potentially time-varying. This approach
allows to model the system parameters as free variables whose values may only
be known within a certain tolerance. We particularly look for minimal
sufficient conditions on the observability and controllability of the composite
network, which have a direct application in distributed estimation and in the
design of networked control systems. The methodology in this paper is based on
the structured systems analysis and graph theory, and therefore, the results
are generic, i.e., they apply to almost all non-zero choices of free
parameters. We show the controllability/observability results for composite
product networks resulting from full structural-rank systems and self-damped
networks. We provide an illustrative example of estimation based on Kalman
filtering over a composite network to verify our results.Comment: Accepted for publication in IEEE TSIP